def pick_scenarios(lnsas, weights, multi, numeps):
'''this function takes some scenarios with an annual rate of occurrence > 10e-5 OR does it based on some other criteria, called get_praveen_results'''
scenarios = []
wout = []
index = 0
easy = True #whether to just take scenarios that are of engineering interest or do some complicated other thing
print 'length of lnsas: ', len(lnsas)
print 'length of weights: ', len(weights)
print 'numeps: ', numeps
wsum = 0
if easy == True:
print 'easy'
for w in weights:
wsum += weights[w]
if weights[w]> 0.00001/float(numeps): #0.0000001/numeps: #10^-5 divided by num eps because the weights get renormalized when take more than one epsilon realization per scenario
scenarios.append(index)
wout.append((index, weights[w]))
index += 1
else:
(scenarios, wout) = get_praveen_results(lnsas)
util.write_2dlist(time.strftime("%Y%m%d")+'_weights_' + str(numeps) + 'eps.txt', wout) #save the weights of the chosen scenarios
print 'number of chosen scenarios: ', len(scenarios)
print 'weights of all scenarios: ', wsum
print 'the sum of the subset weights: ', sum([ww[1] for ww in wout])
return scenarios
def pick_scenarios(lnsas, weights, multi=True):
scenarios = []
wout = []
index = 0
easy = True #whether to just take scenarios that are of engineering interest or do some complicated other thing
print 'length of lnsas: ', len(lnsas)
print 'length of weights: ', len(weights)
numeps = int(round(len(lnsas)/4993.0))
print 'numeps: ', numeps
wsum = 0
if easy == True:
print 'easy'
print 0.00001/float(numeps)
for w in weights:
wsum += weights[w]
print weights[w]
if weights[w]> 0.00001/float(numeps): #0.0000001/numeps: #10^-5 divided by num eps because the weights get renormalized when take more than one epsilon realization per scenario
scenarios.append(index)
wout.append((index, weights[w]))
index += 1
else:
(scenarios, wout) = get_praveen_results(lnsas)
util.write_2dlist(time.strftime("%Y%m%d")+'_weights2.txt', wout) #save the weights of the chosen scenarios
print 'number of chosen scenarios: ', len(scenarios)
print 'weights of all scenarios: ', wsum
print 'the sum of the subset weights: ', sum([ww[1] for ww in wout])
return scenarios